Pan-specific prediction of peptide-MHC Class I complex stability, a correlate of T cell immunogenicity

Autores
Rasmussen, Michael; Fenoy, Luis Emilio; Harndahl, Mikkel; Kristensen, Anne Bregnballe; Nielsen, Ida Kallehauge; Nielsen, Morten; Buus, Søren
Año de publicación
2016
Idioma
inglés
Tipo de recurso
artículo
Estado
versión publicada
Descripción
Binding of peptides to MHC class I (MHC-I) molecules is the most selective event in the processing and presentation of Ags to CTL, and insights into the mechanisms that govern peptide-MHC-I binding should facilitate our understanding of CTL biology. Peptide-MHC-I interactions have traditionally been quantified by the strength of the interaction, that is, the binding affinity, yet it has been shown that the stability of the peptide-MHC-I complex is a better correlate of immunogenicity compared with binding affinity. In this study, we have experimentally analyzed peptide-MHC-I complex stability of a large panel of human MHC-I allotypes and generated a body of data sufficient to develop a neural network-based pan-specific predictor of peptide-MHC-I complex stability. Integrating the neural network predictors of peptide-MHC-I complex stability with state-of-the-art predictors of peptide-MHC-I binding is shown to significantly improve the prediction of CTL epitopes. The method is publicly available at http://www.cbs.dtu.dk/services/NetMHCstabpan.
Fil: Rasmussen, Michael. Universidad de Copenhagen; Dinamarca
Fil: Fenoy, Luis Emilio. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - La Plata. Instituto de Investigaciones Biotecnológicas. Instituto de Investigaciones Biotecnológicas ; Argentina
Fil: Harndahl, Mikkel. Universidad de Copenhagen; Dinamarca
Fil: Kristensen, Anne Bregnballe. Universidad de Copenhagen; Dinamarca
Fil: Nielsen, Ida Kallehauge. Universidad de Copenhagen; Dinamarca
Fil: Nielsen, Morten. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina. Universidad de Copenhagen; Dinamarca
Fil: Buus, Søren. Universidad de Copenhagen; Dinamarca
Materia
Mhc-I
Stability
Predictor
Immunology
Nivel de accesibilidad
acceso abierto
Condiciones de uso
https://creativecommons.org/licenses/by-nc-sa/2.5/ar/
Repositorio
CONICET Digital (CONICET)
Institución
Consejo Nacional de Investigaciones Científicas y Técnicas
OAI Identificador
oai:ri.conicet.gov.ar:11336/49514

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network_name_str CONICET Digital (CONICET)
spelling Pan-specific prediction of peptide-MHC Class I complex stability, a correlate of T cell immunogenicityRasmussen, MichaelFenoy, Luis EmilioHarndahl, MikkelKristensen, Anne BregnballeNielsen, Ida KallehaugeNielsen, MortenBuus, SørenMhc-IStabilityPredictorImmunologyhttps://purl.org/becyt/ford/1.2https://purl.org/becyt/ford/1Binding of peptides to MHC class I (MHC-I) molecules is the most selective event in the processing and presentation of Ags to CTL, and insights into the mechanisms that govern peptide-MHC-I binding should facilitate our understanding of CTL biology. Peptide-MHC-I interactions have traditionally been quantified by the strength of the interaction, that is, the binding affinity, yet it has been shown that the stability of the peptide-MHC-I complex is a better correlate of immunogenicity compared with binding affinity. In this study, we have experimentally analyzed peptide-MHC-I complex stability of a large panel of human MHC-I allotypes and generated a body of data sufficient to develop a neural network-based pan-specific predictor of peptide-MHC-I complex stability. Integrating the neural network predictors of peptide-MHC-I complex stability with state-of-the-art predictors of peptide-MHC-I binding is shown to significantly improve the prediction of CTL epitopes. The method is publicly available at http://www.cbs.dtu.dk/services/NetMHCstabpan.Fil: Rasmussen, Michael. Universidad de Copenhagen; DinamarcaFil: Fenoy, Luis Emilio. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - La Plata. Instituto de Investigaciones Biotecnológicas. Instituto de Investigaciones Biotecnológicas ; ArgentinaFil: Harndahl, Mikkel. Universidad de Copenhagen; DinamarcaFil: Kristensen, Anne Bregnballe. Universidad de Copenhagen; DinamarcaFil: Nielsen, Ida Kallehauge. Universidad de Copenhagen; DinamarcaFil: Nielsen, Morten. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina. Universidad de Copenhagen; DinamarcaFil: Buus, Søren. Universidad de Copenhagen; DinamarcaAmerican Association of Immunologists2016-07info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionhttp://purl.org/coar/resource_type/c_6501info:ar-repo/semantics/articuloapplication/pdfapplication/pdfapplication/pdfhttp://hdl.handle.net/11336/49514Rasmussen, Michael; Fenoy, Luis Emilio; Harndahl, Mikkel; Kristensen, Anne Bregnballe; Nielsen, Ida Kallehauge; et al.; Pan-specific prediction of peptide-MHC Class I complex stability, a correlate of T cell immunogenicity; American Association of Immunologists; Journal of Immunology; 197; 4; 7-2016; 1517-15240022-1767CONICET DigitalCONICETenginfo:eu-repo/semantics/altIdentifier/doi/10.4049/jimmunol.1600582info:eu-repo/semantics/altIdentifier/url/http://www.jimmunol.org/content/197/4/1517info:eu-repo/semantics/openAccesshttps://creativecommons.org/licenses/by-nc-sa/2.5/ar/reponame:CONICET Digital (CONICET)instname:Consejo Nacional de Investigaciones Científicas y Técnicas2025-10-15T15:26:13Zoai:ri.conicet.gov.ar:11336/49514instacron:CONICETInstitucionalhttp://ri.conicet.gov.ar/Organismo científico-tecnológicoNo correspondehttp://ri.conicet.gov.ar/oai/requestdasensio@conicet.gov.ar; lcarlino@conicet.gov.arArgentinaNo correspondeNo correspondeNo correspondeopendoar:34982025-10-15 15:26:13.314CONICET Digital (CONICET) - Consejo Nacional de Investigaciones Científicas y Técnicasfalse
dc.title.none.fl_str_mv Pan-specific prediction of peptide-MHC Class I complex stability, a correlate of T cell immunogenicity
title Pan-specific prediction of peptide-MHC Class I complex stability, a correlate of T cell immunogenicity
spellingShingle Pan-specific prediction of peptide-MHC Class I complex stability, a correlate of T cell immunogenicity
Rasmussen, Michael
Mhc-I
Stability
Predictor
Immunology
title_short Pan-specific prediction of peptide-MHC Class I complex stability, a correlate of T cell immunogenicity
title_full Pan-specific prediction of peptide-MHC Class I complex stability, a correlate of T cell immunogenicity
title_fullStr Pan-specific prediction of peptide-MHC Class I complex stability, a correlate of T cell immunogenicity
title_full_unstemmed Pan-specific prediction of peptide-MHC Class I complex stability, a correlate of T cell immunogenicity
title_sort Pan-specific prediction of peptide-MHC Class I complex stability, a correlate of T cell immunogenicity
dc.creator.none.fl_str_mv Rasmussen, Michael
Fenoy, Luis Emilio
Harndahl, Mikkel
Kristensen, Anne Bregnballe
Nielsen, Ida Kallehauge
Nielsen, Morten
Buus, Søren
author Rasmussen, Michael
author_facet Rasmussen, Michael
Fenoy, Luis Emilio
Harndahl, Mikkel
Kristensen, Anne Bregnballe
Nielsen, Ida Kallehauge
Nielsen, Morten
Buus, Søren
author_role author
author2 Fenoy, Luis Emilio
Harndahl, Mikkel
Kristensen, Anne Bregnballe
Nielsen, Ida Kallehauge
Nielsen, Morten
Buus, Søren
author2_role author
author
author
author
author
author
dc.subject.none.fl_str_mv Mhc-I
Stability
Predictor
Immunology
topic Mhc-I
Stability
Predictor
Immunology
purl_subject.fl_str_mv https://purl.org/becyt/ford/1.2
https://purl.org/becyt/ford/1
dc.description.none.fl_txt_mv Binding of peptides to MHC class I (MHC-I) molecules is the most selective event in the processing and presentation of Ags to CTL, and insights into the mechanisms that govern peptide-MHC-I binding should facilitate our understanding of CTL biology. Peptide-MHC-I interactions have traditionally been quantified by the strength of the interaction, that is, the binding affinity, yet it has been shown that the stability of the peptide-MHC-I complex is a better correlate of immunogenicity compared with binding affinity. In this study, we have experimentally analyzed peptide-MHC-I complex stability of a large panel of human MHC-I allotypes and generated a body of data sufficient to develop a neural network-based pan-specific predictor of peptide-MHC-I complex stability. Integrating the neural network predictors of peptide-MHC-I complex stability with state-of-the-art predictors of peptide-MHC-I binding is shown to significantly improve the prediction of CTL epitopes. The method is publicly available at http://www.cbs.dtu.dk/services/NetMHCstabpan.
Fil: Rasmussen, Michael. Universidad de Copenhagen; Dinamarca
Fil: Fenoy, Luis Emilio. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - La Plata. Instituto de Investigaciones Biotecnológicas. Instituto de Investigaciones Biotecnológicas ; Argentina
Fil: Harndahl, Mikkel. Universidad de Copenhagen; Dinamarca
Fil: Kristensen, Anne Bregnballe. Universidad de Copenhagen; Dinamarca
Fil: Nielsen, Ida Kallehauge. Universidad de Copenhagen; Dinamarca
Fil: Nielsen, Morten. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina. Universidad de Copenhagen; Dinamarca
Fil: Buus, Søren. Universidad de Copenhagen; Dinamarca
description Binding of peptides to MHC class I (MHC-I) molecules is the most selective event in the processing and presentation of Ags to CTL, and insights into the mechanisms that govern peptide-MHC-I binding should facilitate our understanding of CTL biology. Peptide-MHC-I interactions have traditionally been quantified by the strength of the interaction, that is, the binding affinity, yet it has been shown that the stability of the peptide-MHC-I complex is a better correlate of immunogenicity compared with binding affinity. In this study, we have experimentally analyzed peptide-MHC-I complex stability of a large panel of human MHC-I allotypes and generated a body of data sufficient to develop a neural network-based pan-specific predictor of peptide-MHC-I complex stability. Integrating the neural network predictors of peptide-MHC-I complex stability with state-of-the-art predictors of peptide-MHC-I binding is shown to significantly improve the prediction of CTL epitopes. The method is publicly available at http://www.cbs.dtu.dk/services/NetMHCstabpan.
publishDate 2016
dc.date.none.fl_str_mv 2016-07
dc.type.none.fl_str_mv info:eu-repo/semantics/article
info:eu-repo/semantics/publishedVersion
http://purl.org/coar/resource_type/c_6501
info:ar-repo/semantics/articulo
format article
status_str publishedVersion
dc.identifier.none.fl_str_mv http://hdl.handle.net/11336/49514
Rasmussen, Michael; Fenoy, Luis Emilio; Harndahl, Mikkel; Kristensen, Anne Bregnballe; Nielsen, Ida Kallehauge; et al.; Pan-specific prediction of peptide-MHC Class I complex stability, a correlate of T cell immunogenicity; American Association of Immunologists; Journal of Immunology; 197; 4; 7-2016; 1517-1524
0022-1767
CONICET Digital
CONICET
url http://hdl.handle.net/11336/49514
identifier_str_mv Rasmussen, Michael; Fenoy, Luis Emilio; Harndahl, Mikkel; Kristensen, Anne Bregnballe; Nielsen, Ida Kallehauge; et al.; Pan-specific prediction of peptide-MHC Class I complex stability, a correlate of T cell immunogenicity; American Association of Immunologists; Journal of Immunology; 197; 4; 7-2016; 1517-1524
0022-1767
CONICET Digital
CONICET
dc.language.none.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv info:eu-repo/semantics/altIdentifier/doi/10.4049/jimmunol.1600582
info:eu-repo/semantics/altIdentifier/url/http://www.jimmunol.org/content/197/4/1517
dc.rights.none.fl_str_mv info:eu-repo/semantics/openAccess
https://creativecommons.org/licenses/by-nc-sa/2.5/ar/
eu_rights_str_mv openAccess
rights_invalid_str_mv https://creativecommons.org/licenses/by-nc-sa/2.5/ar/
dc.format.none.fl_str_mv application/pdf
application/pdf
application/pdf
dc.publisher.none.fl_str_mv American Association of Immunologists
publisher.none.fl_str_mv American Association of Immunologists
dc.source.none.fl_str_mv reponame:CONICET Digital (CONICET)
instname:Consejo Nacional de Investigaciones Científicas y Técnicas
reponame_str CONICET Digital (CONICET)
collection CONICET Digital (CONICET)
instname_str Consejo Nacional de Investigaciones Científicas y Técnicas
repository.name.fl_str_mv CONICET Digital (CONICET) - Consejo Nacional de Investigaciones Científicas y Técnicas
repository.mail.fl_str_mv dasensio@conicet.gov.ar; lcarlino@conicet.gov.ar
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